Deep reinforcement learning for robotics: A survey of real-world successes

C Tang, B Abbatematteo, J Hu… - Annual Review of …, 2024 - annualreviews.org
Reinforcement learning (RL), particularly its combination with deep neural networks,
referred to as deep RL (DRL), has shown tremendous promise across a wide range of …

Deep reinforcement learning based mobile robot navigation: A review

K Zhu, T Zhang - Tsinghua Science and Technology, 2021 - ieeexplore.ieee.org
Navigation is a fundamental problem of mobile robots, for which Deep Reinforcement
Learning (DRL) has received significant attention because of its strong representation and …

Badgr: An autonomous self-supervised learning-based navigation system

G Kahn, P Abbeel, S Levine - IEEE Robotics and Automation …, 2021 - ieeexplore.ieee.org
Mobile robot navigation is typically regarded as a geometric problem, in which the robot's
objective is to perceive the geometry of the environment in order to plan collision-free paths …

Adaptive power system emergency control using deep reinforcement learning

Q Huang, R Huang, W Hao, J Tan… - IEEE Transactions on …, 2019 - ieeexplore.ieee.org
Power system emergency control is generally regarded as the last safety net for grid security
and resiliency. Existing emergency control schemes are usually designed offline based on …

Search on the replay buffer: Bridging planning and reinforcement learning

B Eysenbach, RR Salakhutdinov… - Advances in neural …, 2019 - proceedings.neurips.cc
The history of learning for control has been an exciting back and forth between two broad
classes of algorithms: planning and reinforcement learning. Planning algorithms effectively …